Sanchez & Hall, a research firm for the real estate industry, studied the relation between x = annual income (in thousands of dollars) and y = sale price of house purchased (in thousands of dollars). A random sample of data was collected from mortgage applications for home sales in the region of the study, and is given in the table. Annual Income House Price 215.7 211 144.7 278.5 319.5 236.8 144.8 204 286.8 Conduct a linear regression. Use the results to answer the following questions. a. What is the value of the correlation coefficient (round to 3 decimal places)? What does the value tell you about the linear relationship between the annual income and the price of house purchased? 97 120 73 107 135 81 72 70 108 Correlation coefficient: .779 This indicates: ४ perfect positive linear correlation fairly strong negative linear correlation very weak negative linear correlation no linear correlation perfect negative linear correlation O fairly strong positive linear correlation very weak positive linear correlation b. What is the equation of the Least Squares line? Round the parameter values (slope and y intercept) to 2 decimal places. ŷ -- 33.44 +2.02x c. If a buyer's annual income increases by $1000, the model's predicted change in DOLLARS of the sale price of the house they will purchase is: a(n) increase (NOTE: be careful of UNITS!) O of $ 2050.64 X
Sanchez & Hall, a research firm for the real estate industry, studied the relation between x = annual income (in thousands of dollars) and y = sale price of house purchased (in thousands of dollars). A random sample of data was collected from mortgage applications for home sales in the region of the study, and is given in the table. Annual Income House Price 215.7 211 144.7 278.5 319.5 236.8 144.8 204 286.8 Conduct a linear regression. Use the results to answer the following questions. a. What is the value of the correlation coefficient (round to 3 decimal places)? What does the value tell you about the linear relationship between the annual income and the price of house purchased? 97 120 73 107 135 81 72 70 108 Correlation coefficient: .779 This indicates: ४ perfect positive linear correlation fairly strong negative linear correlation very weak negative linear correlation no linear correlation perfect negative linear correlation O fairly strong positive linear correlation very weak positive linear correlation b. What is the equation of the Least Squares line? Round the parameter values (slope and y intercept) to 2 decimal places. ŷ -- 33.44 +2.02x c. If a buyer's annual income increases by $1000, the model's predicted change in DOLLARS of the sale price of the house they will purchase is: a(n) increase (NOTE: be careful of UNITS!) O of $ 2050.64 X
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:Sanchez & Hall, a research firm for the real estate industry, studied the relation between x = annual income (in
thousands of dollars) and y = sale price of house purchased (in thousands of dollars). A random sample of data
was collected from mortgage applications for home sales in the region of the study, and is given in the table.
Annual Income House Price
215.7
211
144.7
278.5
319.5
236.8
144.8
204
286.8
Conduct a linear regression. Use the results to answer the following questions.
a. What is the value of the correlation coefficient (round to 3 decimal places)? What does the value tell you about
the linear relationship between the annual income and the price of house purchased?
97
120
73
107
135
81
72
70
108
Correlation coefficient: .779
This indicates:
४
perfect positive linear correlation
fairly strong negative linear correlation
very weak negative linear correlation
no linear correlation
perfect negative linear correlation
O fairly strong positive linear correlation
very weak positive linear correlation
Transcribed Image Text:b. What is the equation of the Least Squares line? Round the parameter values (slope and y intercept) to 2
decimal places.
ŷ
--
33.44 +2.02x
c. If a buyer's annual income increases by $1000, the model's predicted change in DOLLARS of the sale price of
the house they will purchase is:
a(n) increase
(NOTE: be careful of UNITS!)
O of $ 2050.64
X
Expert Solution
Step 1
Given
The data is as follows:
| Annual Income, x | House Price, y |
| 97 | 215.7 |
| 120 | 211 |
| 73 | 144.7 |
| 107 | 278.5 |
| 135 | 319.5 |
| 81 | 236.8 |
| 72 | 144.8 |
| 70 | 204 |
| 108 | 286.8 |
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